U.S. patent application number 15/052556 was filed with the patent office on 2017-08-24 for optimized subset processing for de-duplication.
The applicant listed for this patent is salesforce.com, inc.. Invention is credited to Dai Duong DOAN, Danil DVINOV, Arun Kumar JAGOTA, Chenghung KER, Dmytro KUDRIAVTSEV, Parth VAISHNAV.
Application Number | 20170242891 15/052556 |
Document ID | / |
Family ID | 59629959 |
Filed Date | 2017-08-24 |
United States Patent
Application |
20170242891 |
Kind Code |
A1 |
DOAN; Dai Duong ; et
al. |
August 24, 2017 |
OPTIMIZED SUBSET PROCESSING FOR DE-DUPLICATION
Abstract
Some embodiments of the present invention include a method for
identifying duplicate records from a group of records in a database
system. The method includes generating a cluster of records from a
group of records based on one or more keys; splitting the cluster
of records into multiple subsets of records with each subset of
records having fewer number of records than the cluster of records,
wherein the splitting the cluster of records into multiple subsets
of records is based on a number of records in the cluster of
records exceeding a threshold; causing duplicate sets of records in
each of the subsets of records to be identified, wherein a
duplicate set of records includes one or more records, and wherein
when a duplicate set of records includes two or more records, the
two or more records are duplicates of one another; merging all of
the duplicate sets of records identified from the multiple subsets
of records forming a first group of duplicate sets of records; and
forming a representative set of records based on selecting a
representative record from each of the duplicate sets in the first
group of duplicate sets of records.
Inventors: |
DOAN; Dai Duong; (Alameda,
CA) ; JAGOTA; Arun Kumar; (Sunnyvale, CA) ;
KER; Chenghung; (Burlingame, CA) ; VAISHNAV;
Parth; (Cupertino, CA) ; DVINOV; Danil; (San
Francisco, CA) ; KUDRIAVTSEV; Dmytro; (Belmont,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
salesforce.com, inc. |
San Francisco |
CA |
US |
|
|
Family ID: |
59629959 |
Appl. No.: |
15/052556 |
Filed: |
February 24, 2016 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/2455 20190101;
G06F 7/32 20130101; G06F 16/285 20190101; G06F 16/24556
20190101 |
International
Class: |
G06F 17/30 20060101
G06F017/30; G06F 7/32 20060101 G06F007/32 |
Claims
1. A computer-implemented method comprising: generating, by a
database system, a cluster of records from a group of records based
on one or more keys; splitting, by the database system, the cluster
of records into multiple subsets of records with each subset of
records having fewer number of records than the cluster of records,
wherein the splitting the cluster of records into multiple subsets
of records is based on a number of records in the cluster of
records exceeding a threshold; causing, by the database system,
duplicate sets of records in each of the subsets of records to be
identified, wherein a duplicate set of records includes one or more
records, and wherein when a duplicate set of records includes two
or more records, the two or more records are duplicates of one
another; merging, by the database system, all of the duplicate sets
of records identified from the multiple subsets of records forming
a first group of duplicate sets of records; and forming, by the
database system, a representative set of records based on selecting
a representative record from each of the duplicate sets in the
first group of duplicate sets of records.
2. The method of claim 1, wherein when a duplicate set of records
includes two or more records, any one of the two or more records is
selectable as a representative record, and wherein when a duplicate
set of records includes only one record, the one record is a
representative record.
3. The method of claim 2, wherein merging all of the duplicate sets
of records identified from the multiple subsets of records
comprises merging two duplicate sets of records when the two
duplicate sets of records share a common record.
4. The method of claim 3, wherein merging two duplicate sets of
records comprises: selecting, by the database system, a record from
a first duplicate set of records; comparing, by the database
system, the selected record with each record in a second duplicate
set of records; and merging, by the database system, the first
duplicate set of records with the second duplicate set of records
based on matching the selected record with any one record in the
second duplicate set of records.
5. The method of claim 4, wherein merging the first duplicate set
of records with the second duplicate set of records comprises
merging a duplicate set of records with few records to a duplicate
set of records with more records.
6. The method of claim 5, further comprising: splitting the
representative set of records into multiple subsets of records with
each subset of records having fewer number of records than the
representative set of records when a number of records in the
representative set of records exceeds the threshold; and repeating
the steps of causing duplicate sets of records, merging all the
duplicate sets of records, and forming a representative set with
the multiple subsets of records.
7. The method of claim 5, further comprising: causing duplicate
sets of records in the representative set of records to be
identified forming a second duplicate sets of records; and forming
a third duplicate set of records by merging the first duplicate
sets of records with the second duplicate sets of records.
8. The method of claim 7, wherein a duplicate set of records is
implemented using a linked list having a head node and a body node
for each record in the duplicate set of records, wherein size
information of the duplicate set of records and an identification
information of the duplicate set of records are stored in the head
node, and wherein merging the first duplicate set of records with
the second duplicate set of records comprises merging a linked list
associated with the first duplicate set of records with a linked
list associated with the second duplicate set of records.
9. An apparatus for identifying duplicate records in a database
object, the apparatus comprising: one or more processors; and a
non-transitory computer readable medium storing a plurality of
instructions, which when executed, cause the one or more processors
to: generate a cluster of records from a group of records based on
one or more keys; split the cluster of records into multiple
subsets of records with each subset of records having fewer number
of records than the cluster of records, wherein the splitting the
cluster of records into multiple subsets of records is based on a
number of records in the cluster of records exceeding a threshold;
cause duplicate sets of records in each of the subsets of records
to be identified, wherein a duplicate set of records includes one
or more records, and wherein when a duplicate set of records
includes two or more records, the two or more records are
duplicates of one another; merge all of the duplicate sets of
records identified from the multiple subsets of records forming a
first group of duplicate sets of records; and form a representative
set of records based on selecting a representative record from each
of the duplicate sets in the first group of duplicate sets of
records.
10. The apparatus of claim 9, wherein when a duplicate set of
records includes two or more records, any one of the two or more
records is selectable as a representative record, and wherein when
a duplicate set of records includes only one record, the one record
is a representative record.
11. The apparatus of claim 10, wherein merging all of the duplicate
sets of records identified from the multiple subsets of records
comprises merging two duplicate sets of records when the two
duplicate sets of records share a common record.
12. The apparatus of claim 11, wherein merging two duplicate sets
of records comprises: selecting a record from a first duplicate set
of records; comparing the selected record with each record in a
second duplicate set of records; and merging the first duplicate
set of records with the second duplicate set of records based on
matching the selected record with any one record in the second
duplicate set of records.
13. The apparatus of claim 12, wherein merging the first duplicate
set of records with the second duplicate set of records comprises
merging a duplicate set of records with few records to a duplicate
set of records with more records.
14. The apparatus of claim 13, further comprising: splitting the
representative set of records into multiple subsets of records with
each subset of records having fewer number of records than the
representative set of records when a number of records in the
representative set of records exceeds the threshold; and repeating
the steps of causing duplicate sets of records, merging all the
duplicate sets of records, and forming a representative set with
the multiple subsets of records.
15. The apparatus of claim 13, further comprising: causing
duplicate sets of records in the representative set of records to
be identified forming a second duplicate sets of records; and
forming a third duplicate set of records by merging the first
duplicate sets of records with the second duplicate sets of
records.
16. The apparatus of claim 15, wherein a duplicate set of records
is implemented using a linked list having a head node and a body
node for each record in the duplicate set of records, wherein size
information of the duplicate set of records and an identification
information of the duplicate set of records are stored in the head
node, and wherein merging the first duplicate set of records with
the second duplicate set of records comprises merging a linked list
associated with the first duplicate set of records with a linked
list associated with the second duplicate set of records.
17. A computer program product comprising computer-readable program
code to be executed by one or more processors when retrieved from a
non-transitory computer-readable medium, the program code including
instructions to: generate a cluster of records from a group of
records based on one or more keys; split the cluster of records
into multiple subsets of records with each subset of records having
fewer number of records than the cluster of records, wherein the
splitting the cluster of records into multiple subsets of records
is based on a number of records in the cluster of records exceeding
a threshold; cause duplicate sets of records in each of the subsets
of records to be identified, wherein a duplicate set of records
includes one or more records, and wherein when a duplicate set of
records includes two or more records, the two or more records are
duplicates of one another; merge all of the duplicate sets of
records identified from the multiple subsets of records forming a
first group of duplicate sets of records; and form a representative
set of records based on selecting a representative record from each
of the duplicate sets in the first group of duplicate sets of
records.
18. The computer program product of claim 17, wherein when a
duplicate set of records includes two or more records, any one of
the two or more records is selectable as a representative record,
and wherein when a duplicate set of records includes only one
record, the one record is a representative record.
19. The computer program product of claim 18, wherein merging all
of the duplicate sets of records identified from the multiple
subsets of records comprises merging two duplicate sets of records
when the two duplicate sets of records share a common record.
20. The computer program product of claim 19, wherein merging two
duplicate sets of records comprises: selecting a record from a
first duplicate set of records; comparing the selected record with
each record in a second duplicate set of records; and merging the
first duplicate set of records with the second duplicate set of
records based on matching the selected record with any one record
in the second duplicate set of records.
21. The computer program product of claim 20, wherein merging the
first duplicate set of records with the second duplicate set of
records comprises merging a duplicate set of records with few
records to a duplicate set of records with more records.
22. The computer program product of claim 21, further comprising:
splitting the representative set of records into multiple subsets
of records with each subset of records having fewer number of
records than the representative set of records when a number of
records in the representative set of records exceeding the
threshold; and repeating the steps of causing duplicate sets of
records, merging all the duplicate sets of records, and forming a
representative set with the multiple subsets of records.
23. The computer program product of claim 21, further comprising:
causing duplicate sets of records in the representative set of
records to be identified forming a second duplicate sets of
records; and forming a third duplicate set of records by merging
the first duplicate sets of records with the second duplicate sets
of records.
24. The computer program product of claim 23, wherein a duplicate
set of records is implemented using a linked list having a head
node and a body node for each record in the duplicate set of
records, wherein size information of the duplicate set of records
and an identification information of the duplicate set of records
are stored in the head node, and wherein merging the first
duplicate set of records with the second duplicate set of records
comprises merging a linked list associated with the first duplicate
set of records with a linked list associated with the second
duplicate set of records.
Description
COPYRIGHT NOTICE
[0001] A portion of the disclosure of this patent document contains
material which is subject to copyright protection. The copyright
owner has no objection to the facsimile reproduction by anyone of
the patent document or the patent disclosure, as it appears in the
Patent and Trademark Office patent file or records, but otherwise
reserves all copyright rights whatsoever.
TECHNICAL FIELD
[0002] The present disclosure relates generally to data processing
and more specifically relates to identifying duplicate
information.
BACKGROUND
[0003] The subject matter discussed in the background section
should not be assumed to be prior art merely as a result of its
mention in the background section. Similarly, a problem mentioned
in the background section or associated with the subject matter of
the background section should not be assumed to have been
previously recognized in the prior art. The subject matter in the
background section merely represents different approaches, which in
and of themselves may also be inventions.
[0004] Database systems may include databases that have millions of
records. To maintain the efficiency and integrity of the databases,
searches may be performed to identify and remove duplicate records.
Comparison of records against all the other records one-by-one to
determine duplication may be significantly time consuming and
computing intensive. As such, database designers continuously try
to develop techniques that can improve the performance of the
database as related to identifying and removing duplicate
records.
BRIEF SUMMARY
[0005] For some embodiments, methods and systems for identifying
duplicate records in a database system may include generating a
cluster of records from a group of records based on one or more
keys; splitting the cluster of records into multiple subsets of
records with each subset of records having fewer number of records
than the cluster of records, wherein the splitting the cluster of
records into multiple subsets of records is based on a number of
records in the cluster of records exceeding a threshold; causing
duplicate sets of records in each of the subsets of records to be
identified, wherein a duplicate set of records includes one or more
records, and wherein when a duplicate set of records includes two
or more records, the two or more records are duplicates of one
another; merging all of the duplicate sets of records identified
from the multiple subsets of records forming a first group of
duplicate sets of records; and forming a representative set of
records based on selecting a representative record from each of the
duplicate sets in the first group of duplicate sets of records.
Other aspects and advantages of the present invention can be seen
on review of the drawings, the detailed description and the claims,
which follow.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] The included drawings are for illustrative purposes and
serve only to provide examples of possible structures and process
steps for the disclosed techniques. These drawings in no way limit
any changes in form and detail that may be made to embodiments by
one skilled in the art without departing from the spirit and scope
of the disclosure.
[0007] FIG. 1 shows a diagram of an example computing system that
may be used with some embodiments.
[0008] FIG. 2 shows a diagram of an example network environment
that may be used with some embodiments.
[0009] FIG. 3A shows diagrams of an example of a de-duplication
module, in accordance with some embodiments.
[0010] FIG. 3B shows another example of a de-duplication module
that may be used to identify and remove duplicate records using a
matching service, in accordance with some embodiments.
[0011] FIG. 3C shows another example of a de-duplication module
that may be used to identify and remove duplicate records using
subsets, in accordance with some embodiments.
[0012] FIG. 4 shows an example diagram of the clusters generated by
the clustering module, in accordance with some embodiments.
[0013] FIG. 5A shows an example diagram of the duplicate sets
generated by the duplicate matching module, in accordance with some
embodiments.
[0014] FIG. 5B shows an example diagram of splitting a cluster into
multiple subsets, in accordance with some embodiments.
[0015] FIG. 5C shows an example diagram of relationship among the
cluster, subsets and related duplicate sets, in accordance with
some embodiments.
[0016] FIG. 5D shows an example diagram of using a representative
of a duplicate set to identify duplicate records, in accordance
with some embodiments.
[0017] FIGS. 6A, 6B and 6C show an example diagram of a data
structure that may be used to represent duplicate sets, in
accordance with some embodiments.
[0018] FIG. 7 shows a flowchart of an example process for
identifying duplicate records using clusters, subsets and
representative set, in accordance with some embodiments.
[0019] FIG. 8A shows a system diagram illustrating architectural
components of an applicable environment, in accordance with some
embodiments.
[0020] FIG. 8B shows a system diagram further illustrating
architectural components of an applicable environment, in
accordance with some embodiments.
[0021] FIG. 9 shows a system diagram illustrating the architecture
of a multi-tenant database environment, in accordance with some
embodiments.
[0022] FIG. 10 shows a system diagram further illustrating the
architecture of a multi-tenant database environment, in accordance
with some embodiments.
DETAILED DESCRIPTION
[0023] Applications of systems and methods for identifying
duplicate records in a group of records will be described with
reference to example embodiments. These examples are being provided
solely to add context and aid in the understanding of the present
disclosure. It will thus be apparent to one skilled in the art that
the techniques described herein may be practiced without some or
all of these specific details. In other instances, well known
process steps have not been described in detail in order to avoid
unnecessarily obscuring the present disclosure. Other applications
are possible, such that the following examples should not be taken
as definitive or limiting either in scope or setting.
[0024] In the following detailed description, references are made
to the accompanying drawings, which form a part of the description
and in which are shown, by way of illustration, specific
embodiments. Although these embodiments are described in sufficient
detail to enable one skilled in the art to practice the disclosure,
it is understood that these examples are not limiting, such that
other embodiments may be used and changes may be made without
departing from the spirit and scope of the disclosure.
[0025] As used herein, the term "multi-tenant database system"
refers to those systems in which various elements of hardware and
software of the database system may be shared by one or more
customers. For example, a given application server may
simultaneously process requests for a great number of customers,
and a given database table may store rows for a potentially much
greater number of customers.
[0026] The described subject matter may be implemented in the
context of any computer-implemented system, such as a
software-based system, a database system, a multi-tenant
environment, or the like. Moreover, the described subject matter
may be implemented in connection with two or more separate and
distinct computer-implemented systems that cooperate and
communicate with one another. One or more embodiments may be
implemented in numerous ways, including as a process, an apparatus,
a system, a device, a method, a computer readable medium such as a
computer readable storage medium containing computer readable
instructions or computer program code, or as a computer program
product comprising a computer usable medium having a computer
readable program code embodied therein.
[0027] In general, businesses use a CRM (Customer Relationship
Management) system (also referred to as a database system or
system) to manage business relationships and information associated
with the business relationship. For example, this may include
customer and prospect contact information, accounts, leads, and
opportunities in one central location. The information may be
stored in a database as objects. For example, the CRM system may
include "account" object, "contact" object and "opportunities"
object.
[0028] The "account" object may include information about an
organization or person (such as customers, competitors, and
partners) involved with a particular business. The "contact" object
may include contact information, where each contact may be an
individual associated with an "account". The "opportunities" object
includes information about a sale or a pending deal. Each object
may be associated with fields. For example, the "accounts" object
may include fields such as "company", "zip", "phone number", "email
address", etc. The "contact" object may include fields such as
"first name", "last name", "phone number", "accountID", etc. The
"accountID" field of the "contact" object may be the ID of the
account that is the parent of the contact. The "opportunity" object
may include fields such as "amount", "accountID", etc. The
"accountID" field of the "opportunity" object may be the ID of the
account that is associated with the opportunity. Each field may be
associated with a field value. For example, a field value for the
"zip" field may be "94105".
[0029] There may be millions of records (e.g., individual contacts)
in an object (e.g., contact object). When a new contact is inserted
into the contact object, a match rule (or matching rule) may be
applied to identify duplicate contacts. A match rule may use
criteria to determine how closely a field on a new or edited record
matches the same field on an existing record, and, ultimately,
whether the two records match. A match key may be used by a match
rule to quickly return a list of possible duplicates. The match key
may be based on one or more fields. For example, a match key that
is based on a "company" field and a "zip" field in an "accounts"
object may be "company (2,6) zip (1,3)" with the numbers inside the
brackets referring to number of tokens and number of characters per
token.
[0030] Before the match keys are applied to any objects, the field
values of those objects may be normalized. For example, if the
object includes the field "company", then the normalization for the
field "company" may include expanding the acronyms, having the
first letter of each word be in lowercases, removing the suffices
such as "Corporation", "Incorporated", "Inc", "Limited", "Ltd.",
etc., and removing the stop words such as "and", "the", "of". Using
this normalization example, the field value "Intel Corp." is
normalized to become "intel", and the field value "IBM" is
normalized to become "international business machine".
[0031] After the field values are normalized, some standard or
pre-defined match keys are automatically applied when the match
rule is activated. An example of a pre-defined match key is
"company (2, 6) zip (1, 3)" that is applied to the "account"
object. For example, if the company name is "salesforce.com", then
applying the first portion "company (2, 6)" of the match key
results in the string "salesf", and if the company zip code is
"94105-5188", then applying the second portion "zip (1, 3)" of the
match key results in the string "941". The resulting key is
therefore "salesf941". The process of applying the standard match
keys may be referred to as indexing.
[0032] When the match rule is activated, the match key is
automatically applied to all existing records so that when the
match rule runs, the database system can look for duplicate
candidates among records with the same key. For example, when the
above example match key is applied to the "company" and "zip"
fields, the key "sales941" is generated to match duplicate records
having the same value in the "company" and "zip" fields. Using the
match key to identify duplicate candidates can prevent users from
saving duplicate records based on the value of one or more
fields.
[0033] Using match rules to identify duplicate candidates may be
applicable when adding a new record or an edited record into an
object to determine how closely a field on the new or edited record
matches the same field on an existing record and whether the two
records match. However, this approach may not be applicable when an
organization has millions of records that need to be processed to
remove duplicate records (also referred to as de-duplication or
de-dupe). The identification of the duplicate records can be
challenging and may significantly affect the performance of the CRM
system. As will be described, the millions of records may need to
be grouped into multiple clusters of fewer of records to enable
faster and more efficient identification and removal of the
duplicate records.
[0034] The disclosed embodiments may include systems and methods
for identifying duplicate records in a group of records in a
database system and may include generating a cluster of records
from a group of records based on one or more keys; splitting the
cluster of records into multiple subsets of records with each
subset of records having fewer number of records than the cluster
of records, wherein the splitting the cluster of records into
multiple subsets of records is based on a number of records in the
cluster of records exceeding a threshold; causing duplicate sets of
records in each of the subsets of records to be identified, wherein
a duplicate set of records includes one or more records, and
wherein when a duplicate set of records includes two or more
records, the two or more records are duplicates of one another;
merging all of the duplicate sets of records identified from the
multiple subsets of records forming a first group of duplicate sets
of records; and forming a representative set of records based on
selecting a representative record from each of the duplicate sets
in the first group of duplicate sets of records.
[0035] The disclosed embodiments may include an apparatus for
identifying duplicate records and include a processor, and one or
more stored sequences of instructions which, when executed by the
processor, cause the processor to generate a cluster of records
from a group of records based on one or more keys; split the
cluster of records into multiple subsets of records with each
subset of records having fewer number of records than the cluster
of records, wherein the splitting the cluster of records into
multiple subsets of records is based on a number of records in the
cluster of records exceeding a threshold; cause duplicate sets of
records in each of the subsets of records to be identified, wherein
a duplicate set of records includes one or more records, and
wherein when a duplicate set of records includes two or more
records, the two or more records are duplicates of one another;
merge all of the duplicate sets of records identified from the
multiple subsets of records forming a first group of duplicate sets
of records; and form a representative set of records based on
selecting a representative record from each of the duplicate sets
in the first group of duplicate sets of records.
[0036] The disclosed embodiments may include a machine-readable
medium carrying one or more sequences of instructions for
identifying duplicate records in a group of records in a CRM
system, which instructions, when executed by one or more
processors, may cause the one or more processors to generate a
cluster of records from a group of records based on one or more
keys; split the cluster of records into multiple subsets of records
with each subset of records having fewer number of records than the
cluster of records, wherein the splitting the cluster of records
into multiple subsets of records is based on a number of records in
the cluster of records exceeding a threshold; cause duplicate sets
of records in each of the subsets of records to be identified,
wherein a duplicate set of records includes one or more records,
and wherein when a duplicate set of records includes two or more
records, the two or more records are duplicates of one another;
merge all of the duplicate sets of records identified from the
multiple subsets of records forming a first group of duplicate sets
of records; and form a representative set of records based on
selecting a representative record from each of the duplicate sets
in the first group of duplicate sets of records.
[0037] While one or more implementations and techniques are
described with reference to an embodiment in which identifying
duplicate records using clustering, subsets, and duplicate sets is
implemented in a system having an application server providing a
front end for an on-demand database service capable of supporting
multiple tenants, the one or more implementations and techniques
are not limited to multi-tenant databases nor deployment on
application servers. Embodiments may be practiced using other
database architectures, i.e., ORACLE.RTM., DB2.RTM. by IBM and the
like without departing from the scope of the embodiments
claimed.
[0038] Any of the above embodiments may be used alone or together
with one another in any combination. The one or more
implementations encompassed within this specification may also
include embodiments that are only partially mentioned or alluded to
or are not mentioned or alluded to at all in this brief summary or
in the abstract. Although various embodiments may have been
motivated by various deficiencies with the prior art, which may be
discussed or alluded to in one or more places in the specification,
the embodiments do not necessarily address any of these
deficiencies. In other words, different embodiments may address
different deficiencies that may be discussed in the specification.
Some embodiments may only partially address some deficiencies or
just one deficiency that may be discussed in the specification, and
some embodiments may not address any of these deficiencies.
[0039] The described subject matter may be implemented in the
context of any computer-implemented system, such as a
software-based system, a database system, a multi-tenant
environment, or the like. Moreover, the described subject matter
may be implemented in connection with two or more separate and
distinct computer-implemented systems that cooperate and
communicate with one another. One or more implementations may be
implemented in numerous ways, including as a process, an apparatus,
a system, a device, a method, a computer readable medium such as a
computer readable storage medium containing computer readable
instructions or computer program code, or as a computer program
product comprising a computer usable medium having a computer
readable program code embodied therein.
[0040] FIG. 1 is a diagram of an example computing system that may
be used with some embodiments of the present invention. The
computing system 102 may be used by a user to initiate identifying
and removing duplicate records associated with a multi-tenant
database environment. For example, the multi-tenant database
environment may be associated with the services provided by
Salesforce.com.RTM..
[0041] The computing system 102 is only one example of a suitable
computing system, such as a mobile computing system, and is not
intended to suggest any limitation as to the scope of use or
functionality of the design. Neither should the computing system
102 be interpreted as having any dependency or requirement relating
to any one or combination of components illustrated. The design is
operational with numerous other general purpose or special purpose
computing systems. Examples of well-known computing systems,
environments, and/or configurations that may be suitable for use
with the design include, but are not limited to, personal
computers, server computers, hand-held or laptop devices,
multiprocessor systems, microprocessor-based systems, set top
boxes, programmable consumer electronics, mini-computers, mainframe
computers, distributed computing environments that include any of
the above systems or devices, and the like. For example, the
computing system 102 may be implemented as a mobile computing
system such as one that is configured to run with an operating
system (e.g., iOS) developed by Apple Inc. of Cupertino, Calif. or
an operating system (e.g., Android) that is developed by Google
Inc. of Mountain View, Calif.
[0042] Some embodiments of the present invention may be described
in the general context of computing system executable instructions,
such as program modules, being executed by a computer. Generally,
program modules include routines, programs, objects, components,
data structures, etc. that performs particular tasks or implement
particular abstract data types. Those skilled in the art can
implement the description and/or figures herein as
computer-executable instructions, which can be embodied on any form
of computing machine readable media discussed below.
[0043] Some embodiments of the present invention may also be
practiced in distributed computing environments where tasks are
performed by remote processing devices that are linked through a
communications network. In a distributed computing environment,
program modules may be located in both local and remote computer
storage media including memory storage devices.
[0044] Referring to FIG. 1, the computing system 102 may include,
but are not limited to, a processing unit 120 having one or more
processing cores, a system memory 130, and a system bus 121 that
couples various system components including the system memory 130
to the processing unit 120. The system bus 121 may be any of
several types of bus structures including a memory bus or memory
controller, a peripheral bus, and a local bus using any of a
variety of bus architectures. By way of example, and not
limitation, such architectures include Industry Standard
Architecture (ISA) bus, Micro Channel Architecture (MCA) bus,
Enhanced ISA (EISA) bus, Video Electronics Standards Association
(VESA) locale bus, and Peripheral Component Interconnect (PCI) bus
also known as Mezzanine bus.
[0045] The computing system 102 typically includes a variety of
computer readable media. Computer readable media can be any
available media that can be accessed by computing system 102 and
includes both volatile and nonvolatile media, removable and
non-removable media. By way of example, and not limitation,
computer readable media may store information such as computer
readable instructions, data structures, program modules or other
data. Computer storage media include, but are not limited to, RAM,
ROM, EEPROM, flash memory or other memory technology, CD-ROM,
digital versatile disks (DVD) or other optical disk storage,
magnetic cassettes, magnetic tape, magnetic disk storage or other
magnetic storage devices, or any other medium which can be used to
store the desired information and which can be accessed by
computing system 102. Communication media typically embodies
computer readable instructions, data structures, or program
modules.
[0046] The system memory 130 may include computer storage media in
the form of volatile and/or nonvolatile memory such as read only
memory (ROM) 131 and random access memory (RAM) 132. A basic
input/output system (BIOS) 133, containing the basic routines that
help to transfer information between elements within computing
system 102, such as during start-up, is typically stored in ROM
131. RAM 132 typically contains data and/or program modules that
are immediately accessible to and/or presently being operated on by
processing unit 120. By way of example, and not limitation, FIG. 1
also illustrates operating system 134, application programs 135,
other program modules 136, and program data 137.
[0047] The computing system 102 may also include other
removable/non-removable volatile/nonvolatile computer storage
media. By way of example only, FIG. 1 also illustrates a hard disk
drive 141 that reads from or writes to non-removable, nonvolatile
magnetic media, a magnetic disk drive 151 that reads from or writes
to a removable, nonvolatile magnetic disk 152, and an optical disk
drive 155 that reads from or writes to a removable, nonvolatile
optical disk 156 such as, for example, a CD ROM or other optical
media. Other removable/non-removable, volatile/nonvolatile computer
storage media that can be used in the exemplary operating
environment include, but are not limited to, USB drives and
devices, magnetic tape cassettes, flash memory cards, digital
versatile disks, digital video tape, solid state RAM, solid state
ROM, and the like. The hard disk drive 141 is typically connected
to the system bus 121 through a non-removable memory interface such
as interface 140, and magnetic disk drive 151 and optical disk
drive 155 are typically connected to the system bus 121 by a
removable memory interface, such as interface 150.
[0048] The drives and their associated computer storage media
discussed above and illustrated in FIG. 1, provide storage of
computer readable instructions, data structures, program modules
and other data for the computing system 102. In FIG. 1, for
example, hard disk drive 141 is illustrated as storing operating
system 144, application programs 145, other program modules 146,
and program data 147. Note that these components can either be the
same as or different from operating system 134, application
programs 135, other program modules 136, and program data 137. The
operating system 144, the application programs 145, the other
program modules 146, and the program data 147 are given different
numeric identification here to illustrate that, at a minimum, they
are different copies.
[0049] A user may enter commands and information into the computing
system 102 through input devices such as a keyboard 162, a
microphone 163, and a pointing device 161, such as a mouse,
trackball or touch pad or touch screen. Other input devices (not
shown) may include a joystick, game pad, scanner, or the like.
These and other input devices are often connected to the processing
unit 120 through a user input interface 160 that is coupled with
the system bus 121, but may be connected by other interface and bus
structures, such as a parallel port, game port or a universal
serial bus (USB). A monitor 191 or other type of display device is
also connected to the system bus 121 via an interface, such as a
video interface 190. In addition to the monitor, computers may also
include other peripheral output devices such as speakers 197 and
printer 196, which may be connected through an output peripheral
interface 190.
[0050] The computing system 102 may operate in a networked
environment using logical connections to one or more remote
computers, such as a remote computer 180. The remote computer 180
may be a personal computer, a hand-held device, a server, a router,
a network PC, a peer device or other common network node, and
typically includes many or all of the elements described above
relative to the computing system 102. The logical connections
depicted in
[0051] FIG. 1 includes a local area network (LAN) 171 and a wide
area network (WAN) 173, but may also include other networks. Such
networking environments are commonplace in offices, enterprise-wide
computer networks, intranets and the Internet.
[0052] When used in a LAN networking environment, the computing
system 102 may be connected to the LAN 171 through a network
interface or adapter 170. When used in a WAN networking
environment, the computing system 102 typically includes a modem
172 or other means for establishing communications over the WAN
173, such as the Internet. The modem 172, which may be internal or
external, may be connected to the system bus 121 via the user-input
interface 160, or other appropriate mechanism. In a networked
environment, program modules depicted relative to the computing
system 102, or portions thereof, may be stored in a remote memory
storage device. By way of example, and not limitation, FIG. 1
illustrates remote application programs 185 as residing on remote
computer 180. It will be appreciated that the network connections
shown are exemplary and other means of establishing a
communications link between the computers may be used.
[0053] It should be noted that some embodiments of the present
invention may be carried out on a computing system such as that
described with respect to FIG. 1. However, some embodiments of the
present invention may be carried out on a server, a computer
devoted to message handling, handheld devices, or on a distributed
system in which different portions of the present design may be
carried out on different parts of the distributed computing
system.
[0054] Another device that may be coupled with the system bus 121
is a power supply such as a battery or a Direct Current (DC) power
supply) and Alternating Current (AC) adapter circuit. The DC power
supply may be a battery, a fuel cell, or similar DC power source
needs to be recharged on a periodic basis. The communication module
(or modem) 172 may employ a Wireless Application Protocol (WAP) to
establish a wireless communication channel. The communication
module 172 may implement a wireless networking standard such as
Institute of Electrical and Electronics Engineers (IEEE) 802.11
standard, IEEE std. 802.11-1999, published by IEEE in 1999.
[0055] Examples of mobile computing systems may be a laptop
computer, a tablet computer, a Netbook, a smart phone, a personal
digital assistant, or other similar device with on board processing
power and wireless communications ability that is powered by a
Direct Current (DC) power source that supplies DC voltage to the
mobile computing system and that is solely within the mobile
computing system and needs to be recharged on a periodic basis,
such as a fuel cell or a battery.
[0056] FIG. 2 shows a diagram of an example network environment
that may be used with some embodiments of the present invention.
Network environment 400 includes computing systems 205 and 212. One
or more of the computing systems 205 and 212 may be a mobile
computing system. The computing systems 205 and 212 may be
connected to the network 250 via a cellular connection or via a
Wi-Fi router (not shown). The network 250 may be the Internet. The
computing systems 205 and 212 may be coupled with server computing
system 255 via the network 250.
[0057] The computing systems 205 may include application module
208. A user may use the computing system 205 and the application
module 208 to connect to and communicate with the server computing
system 255 and log into application 257 (e.g., a
Salesforce.com.RTM. application). For example, the user may log
into the application 257 to initiate the process of identifying and
removing duplicate records in a group of records in a CRM system.
The server computing system 255 may be coupled with database 270.
The server computing system 255 may be associated with an entity
(e.g., Salesforce.com.RTM.).
[0058] FIG. 3A shows an example of a de-duplication module that may
be used to identify and remove duplicate records, in accordance
with some embodiments. De-duplication module 300 may be associated
with a computing system that is used by an administrator or a user
who is responsible for removing duplicate records in a group of
records 302. For some embodiments, the group of records 302 may be
legacy records associated with a customer or an organization, and
the de-duplication module 300 is configured to identify all of the
duplicate records in the group and remove them. The group of
records 302 may be stored in a database such as database 270 shown
in FIG. 2. The group of records 302 may be associated with a
web-based customer relationship management (CRM) database system
916 shown in FIG. 9.
[0059] The de-duplication module 300 may include clustering module
310 configured to generate multiple clusters from a group of
records 302. For some embodiments, the records in the group of
records 302 may be keyed into multiple keys. For example, when the
records are employee records, the multiple keys may be associated
with a last name, first name, account name, etc. The clustering
module 310 may use match rules based on one or more keys to
generate clusters of records. For example, when using a match rule
that is keyed on the last name and based on a particular key value
for last name (e.g., "Smith"), a first cluster of match candidates
may be generated containing all records that have the same last
name "Smith". When using the same match rule that is keyed on the
last name and based on a different key value ("Brown"), a second
cluster of match candidates may be generated containing all records
that have the same last name "Brown". When using a match rule that
is keyed on the account name and based on a particular key value
for account name (e.g., "Salesforce.com.RTM."), a third cluster of
match candidates may be generated containing all records that have
the same account name "Salesforce.com.RTM.". It may be possible
that the same record may be included in more than one cluster. That
is, records in the different clusters may not be mutually
exclusive. For example, a record having the last name value of
"Smith" and the account name value of "Salesforce.com.RTM." can be
included in both the first cluster and the third cluster.
[0060] Using the clustering module 310 is advantageous because it
filters the group of records 302 into clusters of duplicate
candidates, each possibly having fewer (or a subset of) records
comparing to the number of records in the group of records 302,
making it easier to identify the actual duplicate records. For some
embodiments, one or more keys may be used to generate the clusters.
For example, there may be keys based on the last name and the
account name.
[0061] A cluster generated by the clustering module 310 based on
multiple keys may include fewer number of records than the clusters
that are generated based on only one key. However, when the number
of records is large and multiple keys are used, the process of
generating a cluster of duplicate candidates may be time consuming
and may not be as efficient generating clusters using fewer numbers
of keys.
[0062] The de-duplication module 300 may include a duplicate
matching module 315 configured to process the clusters generated by
the clustering module 310. The duplicate matching module 315 may
evaluate each record in a cluster and compare it with other records
in the same cluster to identify duplicates. The matching operations
performed by the duplicate matching module 315 may be referred to
as deep matching because it filters the records included in the
cluster to identify better duplicate candidates.
[0063] The duplicate matching module 315 may generate one or more
duplicate sets for each cluster. Each duplicate set may include one
or more records. A duplicate set with only one record may indicate
that the record is unique within a given cluster. A duplicate set
with multiple records may indicate that all those records are
duplicates of one another within a given cluster. For example,
assuming that there are two clusters, the duplicate matching module
315 may generate three duplicate sets after processing the first
cluster and five duplicate sets after processing the second
cluster, for a total of eight duplicate sets. Because the first and
second clusters are generated based on different keys or key
values, it is possible that the same record may be included in
multiple duplicate sets.
[0064] The de-duplication module 300 may include a duplicate set
merging module 320 configured to evaluate the duplicate sets
generated by the duplicate matching module 315 and perform merging
or consolidation of duplicate sets when necessary. The duplicate
set merging module 320 may select a record in a duplicate set and
determine of the same record exists in another duplicate set. If
that situation exists, it may indicate that all of the records in
the two duplicate sets are the same, and the two duplicate sets may
be merged into a single duplicate set. It may be noted that once
the duplicate set merging module 320 determines that the same
record exists in two different duplicate sets, the merging
operation may be performed without having to evaluate the other
records in the two duplicate sets.
[0065] The de-duplication module 300 may include a duplicate
removal module 325 configured to evaluate the duplicate sets after
they are processed by the duplicate set merging module 320. It may
be noted that each record in the group of records 302 including
those included in the duplicate sets is associated with a unique
address where it is stored in the database system. The address
remains the same and does not change during the operation of the
de-duplication module 300. For some embodiments, the duplicate
removal module 325 may use the address information of the records
in the duplicate sets to remove the duplicate records from the
group of records 302.
[0066] FIG. 3B shows another example of a de-duplication module
that may be used to identify and remove duplicate records using a
matching service, in accordance with some embodiments.
De-duplication module 301 is similar to the de-duplication module
300 of FIG. 3A except for the operation of the duplicate matching
module 315 of FIG. 3A. Instead, the duplicate matching operations
are performed by an external or third party matching service 316
which may be equipped to perform such matching operations more cost
effectively. One example of such third party matching service is
Pitney Bowes.RTM. with its Spectrum platform. It is possible that
the external or third party matching service 316 may impose some
requirements as to the number of records that it can receive and
process. For example, the group of records 302 may include a
million records, while the external or third party matching service
316 may only be able to perform matching operation for a group of
100,000 records at a time. Using this same example, it may be
necessary for the clusters to be sufficiently filtered to have no
more than 100,000 records per cluster. From the external or third
party service 316, duplicate sets 319 may then be received and
processed by the duplicate set merging module 320.
[0067] FIG. 3C shows another example of a de-duplication module
that may be used to identify and remove duplicate records using
subsets, in accordance with some embodiments. De-duplication module
303 is similar to the de-duplication module 300 of FIGS. 3A and 3B
except for the additional subsetting module 311. Instead of
transmitting the clusters from the clustering module 310 to the
duplicate matching module 315 or the third party matching service
316, the clusters transmitted to the subsetting module 311 to split
into multiple subsets. This may be necessary because the number of
records in a cluster may vary and can be very large such that those
records cannot be handled by the duplicate matching module 315 or
the third party matching service 316. For some embodiments, a
threshold may be used to determine whether the clusters need to be
transmitted to the subsetting module 311. As shown in FIG. 3C, the
subsets 313 from the subsetting module 311 may be transmitted to
the duplicate matching module 315. Similarly, the subsets 312 from
the subsetting module 311 may be transmitted to the duplicate
matching service 316.
[0068] FIG. 4A shows an example diagram of the clusters generated
by the clustering module, in accordance with some embodiments. The
clustering module 310 may filter the group of records 302 to
identify duplicate candidates. This may include identifying
clusters of records based on keys and key values. All records that
have a particular value (e.g., "Smith") for the same key (e.g.,
last name) belong to the same cluster. For example, using a first
key value, the clustering module 310 may generate a first cluster
of records 405. Using a second key value, the clustering module 310
may generate a second cluster of records 410. Using a third key
value, the clustering module 310 may generate a third cluster of
records 415.
[0069] FIG. 5A shows an example diagram of the duplicate sets
generated by the duplicate matching module, in accordance with some
embodiments. In the example, the group of records 502 may include
ten records as follows: [0070] "A", "B", "C", "D", "E", "F", "G",
"H", "I" and "J". The group of records 502 may be filtered for
duplicate candidates by the clustering module 310 (shown in FIG. 3)
using key and key values. This generates the clusters 503 and 504.
The cluster 503 may include the records "A", "D", "E", "B", "C" and
"F". The cluster 503 may then be processed by the duplicate
matching module 315 (or third party matching service 316)
generating two duplicate sets 505 and 510. The duplicate set 505
may include the records: [0071] "A", "D" and "E". The duplicate set
510 may include the records: [0072] "B", "C" and "F". The cluster
504 may include the records "G", "H", "E", "I", "J" and "C". The
cluster 504 may then be processed by the duplicate matching module
315 (or third party matching service 316) generating two duplicate
sets 515 and 520. The duplicate set 515 may include the records:
[0073] "G", "H" and "E". The duplicate set 520 may include the
records: [0074] "I", "J" and "C". It may be noted that the record
"E" is common in both the duplicate set 505 and 515, and the record
"C" is common in both the duplicate set 510 and 520.
[0075] FIG. 5B shows an example diagram of splitting a cluster into
multiple subsets, in accordance with some embodiments. It may be
possible that the number of records in a cluster generated by the
clustering module 310 may be too many that it may not be possible
for these records to be efficiently processed by the duplicate
matching module 315 (or the external or third party matching
service 316). For example, a cluster may have 100,000 records while
the matching module 315 may only be able to handle 10,000 records
at a time. For some embodiments, it may be necessary for the
records in a cluster to be split into multiple subsets, with each
subset having fewer records. A threshold may be used to determine
when splitting into smaller subsets may be necessary.
[0076] In general, the smaller the number of records in a subset,
the less time it takes for the duplicate matching module 315 (or
third party matching service 316) to identify and generate the
duplicate sets. However, when the number of records in a subset is
too small, the database system may require more time to merge the
duplicate sets generated by the duplicate matching module 315 (or
third party matching service 316). As shown in the example of FIG.
5B, the cluster 525 (generated by the clustering module 310) is
shown to have ten records A, B, C, D, E, F G, J and I. The cluster
525 is split into "k choose 3" subsets or four (k=4) subsets,
including subset 526 (with records A, B, C), subset 527 (with
records D, E, F), subset 528 (with records G, H, K) and subset 529
(with record J). For some embodiments, there may be no overlapping
of any record among the subsets, i.e., a record may not be included
in two different subsets.
[0077] FIG. 5C shows an example diagram of relationship among the
cluster, subsets and related duplicate sets, in accordance with
some embodiments. For some embodiments, each of the subsets 526-529
may be processed by the duplicate matching module 315 (or third
party matching service 316) to identify duplicate sets. For
example, duplicate sets 530 may be generated from the subset 526.
Similarly, duplicates sets 531 may be generated from the subset
527, duplicate sets 532 generated from the subset 528, and
duplicate set 533 generated from the subset 529. For some
embodiments, the duplicate sets generated from the subsets may be
merged together into a merged duplicate set. For example, the
duplicate sets 530-533 are merged into a merged duplicate sets 555
to include seven duplicate sets {{A, B}, C, D, E, F, {G, H, I},
J}.
[0078] FIG. 5D shows an example diagram of using a representative
of a duplicate set to identify duplicate records, in accordance
with some embodiments. As shown in FIG. 5D, the seven duplicate
sets in the merged duplicate sets 555 (shown in FIG. 5C) are shown
individually as duplicate sets 571-577. For some embodiments, any
one record from a duplicate set is selected as a representative of
the duplicate set. For example, the representative of the duplicate
set 571 is the record "B" (shown in larger font size), and the
representative of the duplicate set 576 is the record "H" (shown in
larger font size). When a duplicate set has only one record, that
record itself is the representative of the duplicate set. The
representatives of all the duplicate sets are grouped together to
form a representative set 580. In this example, the representative
set 580 includes the records B, C, D, E, F, H and J.
[0079] For some embodiments, when the number of records in the
representative set 580 is still too large for the duplicate
matching module 315 (or third party matching service 316) to
identify duplicate sets, the representative 580 may be split into
smaller subsets. A threshold may be used to determine when
splitting into smaller subsets may be necessary. It may be noted
that the evaluation of the number of records in the representative
set, the splitting of the representative set into smaller subsets,
the processing of the subsets and the forming of another
representative set shown in FIGS. 5C and 5D may be repeated until
the number of records in the representative set is acceptable to be
processed by the duplicate matching module 315 (or third party
matching service 316).
[0080] When the representative set 580 is processed by the
duplicate matching module 315 (or third party matching service
316), a duplicate set 585 may be generated. For example, the
duplicate sets 585 may include the following duplicate sets {B,H},
{C}, {D,J}, and {E,F}. As may be noted in FIG. 5D, the duplicate
sets 585 is derived from the representative set 580 which itself is
derived from the merged duplicate set 555. For some embodiments,
the duplicate sets 585 identified from the representative set 580
may be merged with the merged duplicate set 555 to form the
duplicate set 595 as follows:
Duplicate sets 585: {B,H}, {C}, {D,J}, and {E,F} Duplicate sets
555: {{A, B}, C, D, E, F, {G, H, I}, J} Since the duplicate sets
{B,H} and {A,B} share a common record B, they are merged to become
{A,B,H}. Records that have been identified as duplicates remain in
their duplicate sets. A record that is not a duplicate of any other
records remains as a single record in its duplicate set. The merged
or combined duplicate set 595 then includes the duplicate sets
{A,B,H}, {C}, {D,J}, {E, F} and {G,H,I}. For some embodiments, the
process of merging the duplicate sets 585 and the duplicate sets
555 may be repeated for each representative set 580 when a
representative set 580 is split into multiple subsets.
[0081] FIG. 6A shows an example diagram of a data structure that
may be used to represent duplicate sets, in accordance with some
embodiments. As shown, there are four duplicate sets 645, 650, 655
and 660, each corresponding to the respective duplicate sets 505,
510, 515 and 520 shown in FIG. 5A. For some embodiments, each
duplicate set may be implemented as a linked list with a head node
followed by body nodes representing each record in the duplicate
set. For example, the duplicate set 645 is implemented with a head
node 601 followed by three body nodes 621, 622 and 623, with each
corresponding to the respective records "A", "D" and "E".
[0082] A head node may include identification information for the
associated duplicate set. For example, the head node 601 includes
the value "0" as the identification information for the duplicate
set 645. Similarly, the head node 602 includes the value "1" as the
identification information for the duplicate set 650. Each head
node may include information about the number of records included
in (or the size of) the duplicate set. For example, the head node
601 includes the value "3" as the number of records in the
duplicate set 645, and the head node 602 also includes the value
"3" as the number of records in the duplicate set 650. Each head
node may include a body pointer that links the head node to a first
body node in the duplicate set. For example, the head node 601
includes a next node pointer 619 that links the head node 601 to
the body node 621. The duplicate sets 645, 650, 655 and 660 are
considered to be non-empty. When a duplicate set is empty, the body
pointer may not be linked to any body node (e.g., its value may be
set to null). For example, the body pointer of the head node 605
may be set to null.
[0083] A head node may also include a duplicate set pointer that
links the head node to a head node of another duplicate set. For
example, the head node 601 includes the duplicate set pointer 606
that links the head node 601 to the head node 602. The value of the
duplicate set pointer 606 of the head node 605 may be set to null
when there is no other head node to link to. Each head node many
include information about a number of records included in (or the
size of) the duplicate set. For example, the head node 601 includes
the value "3" as the number of records for the records "A", "D" and
"E" in the duplicate set 645, and the head node 602 also includes
the value "3" as the number of records for the records "B", "C" and
"F" in the duplicate set 650.
[0084] A body node may include information about a particular
record in the duplicate set. For example, the body node 621
includes the value "A" as the information for the first record in
the duplicate set 645. Similarly, the body node 622 includes the
value "D" as the information for the second record in the duplicate
set 645, and the body node 623 includes the value "E" as the
information for the third record in the duplicate set 645. Each
body node may include information about the duplicate set that it
belongs to. This may include storing the identification information
of the duplicate set. For example, each of the body nodes 621, 622
and 623 includes the value "0" as the identification information
for the duplicate set 645. For some embodiments, this may include
having a pointer that links to the corresponding head node. For
example, instead of storing the value "0", a head node pointer may
be stored linking a body node such as the body node 622 to the head
node 601. Each body node may include a next node pointer (e.g.,
next node pointer 620 of the body node 621) to point to the next
body node in the duplicate set. The value of the next node pointer
of the last body node in the duplicate set may be set to null. From
the data structure shown in FIG. 6A, it may be noted that the
record "E" is in both the duplicate sets 645 and 655, and the
record "C" is in both the duplicate sets 650 and 660. It may be
noted that even though the duplicate sets shown in FIG. 4 have the
same size as "3", it is possible for the duplicate sets to have
difference sizes. For example, there may be a duplicate set with
only one record. This may indicate that the record is unique within
the cluster that was processed by the duplicate matching module 315
shown in FIG. 3A (or third party matching service 316 shown in FIG.
3B). For some embodiments, all the duplicate sets from all the
clusters associated with the same group of records may be sorted
based on the size of the duplicate sets. For example, the sorting
may be based on an increasing size and may yield a duplicate set
with the least number of records at the top of a sorted list.
Merging may then be performed by starting with the duplicate sets
positioned toward the top of the sorted list. For example, assuming
there is a common duplicate set, a first duplicate set may be
merged with a second duplicate set resulting in a combined
duplicate set. The combined duplicate set may then be merged with a
third duplicate set, and so on.
[0085] FIG. 6B shows an example diagram of a data structure
reflecting the merging of two duplicate sets, in accordance with
some embodiments. For some embodiments, the merging of duplicate
sets may begin with selecting a record in a duplicate set and
determine if that record also exists in another duplicate set. For
example, when it is determined that the record "E" is common in
both the duplicate sets 645 and 655, the duplicate sets 655 may be
merged to the duplicate set 645, with the merged result shown as
duplicate set 665 in FIG. 6B. It may be noted that the merged
duplicate set 665 has five records "A", "D", "E", "G" and "H", and
the size information is updated in the corresponding head node 601
as "5". It may also be noted that the head node 603 is updated to
reflect that it is associated with an empty duplicate set with size
of "0" and with its next node pointer set to null.
[0086] For some embodiments, merging may occur by merging a
duplicate set with few records to a duplicate set with more
records. This approach is efficient as there are fewer nodes to
merge, as compared to merging a duplicate set with more records to
a duplicate set with few records. To determine the size of the two
duplicate sets and which duplicate set has more records, the size
information stored in the corresponding head nodes is evaluated.
For some embodiments, merging may occur by setting the next node
pointer of the last body node of one duplicate set to the first
body node of the other duplicate set.
[0087] FIG. 6C shows an example diagram of a data structure
reflecting the merging of two other duplicate sets, in accordance
with some embodiments. For example, when it is determined that the
record "C" is common in both the duplicate sets 650 and 660, the
duplicate sets 660 may be merged to the duplicate set 650, the
merged result shown as duplicate set 670 in FIG. 6C. It may be
noted that the merged duplicate set 670 has five records "B", "C",
"F", "I" and "J", and this size information is updated in the
corresponding head node 602 as "5". It may be noted that as soon as
the record "C" in the duplicate set 660 is determined to also exist
in the duplicate set 650, no further comparison is necessary with
the other records in the duplicate set 650 because all records in
both the duplicate sets 650 and 660 are transitively the same. It
may also be noted that the head node 604 is updated to reflect that
it is associated with an empty duplicate set with size of "0" and
with its next node pointer set to null. When the merging operation
is completed, each of the records in the group of records (e.g.,
group of records 502 shown in FIG. 5A) is accounted for in exactly
one duplicate set.
[0088] FIG. 7 shows a flowchart of an example process for
generating duplicate sets, in accordance with some embodiments. The
example process 700 may be used to evaluate a group of records to
determine whether the group of records includes duplicate records.
The group of records may be associated with an organization and may
need to be incorporated into a CRM database system. The records in
the group of records may be indexed based on keys. The process may
start at block 705 where the group of records may be evaluated
based on a key (e.g., last name) and key value (e.g., Smith). All
of the records matching the first value may then be grouped
together to form a cluster. An example is shown as the clusters
503, 504 in FIG. 5A.
[0089] At block 710, it is determined that the number of records in
the cluster is more than can be efficiently processed by the
duplicate matching module 315 (or third party matching service
316). As a result, the cluster is split into multiple subsets, with
each subset having fewer records than the number of records in the
cluster. An example is shown as the multiple subsets 526-529 in
FIG. 5B.
[0090] At block 715, each of the subsets is transmitted to the
duplicate matching module 315 (or third party matching service 316)
to generate duplicate sets. Each duplicate set may include one or
more records. Records in the same duplicate set are considered to
be the same. An example is shown as the duplicate sets 530-533 in
FIG. 5C.
[0091] At block 720, the duplicate sets generated from the subsets
are merged together to form merged duplicate sets. Duplicate sets
that share a common record may be merged to one another. Duplicate
sets that have a single record may remain the same. An example is
shown as the merged duplicate sets 555 in FIG. 5C. The merged
duplicate sets may be referred to as a first duplicate set. An
example is shown as the duplicate set 555 in FIG. 5D.
[0092] At block 725, a representative from each of the duplicate
sets in the merged duplicate sets is selected to form a
representative set. An example is shown as the representative set
580 in FIG. 5D. At block 730, the representative set may be
processed by the duplicate matching module 315 (or third party
matching service 316) to form a group of duplicate sets. This may
be referred to as a second group of duplicate sets. An example is
shown as the duplicate sets 585 in FIG. 5D. At block 735, the first
group of duplicate sets and the second group of duplicate sets may
be merged to one another to generate a combined duplicate set. An
example is shown as the combined duplicate sets 595 in FIG. 5D. One
or more records in a merged duplicate list may be removed to
prevent redundancy. Removing a record from a merged duplicate list
may include removing that record from the group of records (e.g.,
group of records 502 shown in FIG. 5A). As described with FIG. 5D,
it may be possible that the number of records in the representative
set may need to be split into subsets. When that occurs, the
process may flow from block 725 to block 710 (shown as the dotted
line 740).
[0093] FIG. 8A shows a system diagram 800 illustrating
architectural components of an on-demand service environment, in
accordance with some embodiments. A client machine located in the
cloud 804 (or Internet) may communicate with the on-demand service
environment via one or more edge routers 808 and 812. The edge
routers may communicate with one or more core switches 820 and 824
via firewall 816. The core switches may communicate with a load
balancer 828, which may distribute server load over different pods,
such as the pods 840 and 844. The pods 840 and 844, which may each
include one or more servers and/or other computing resources, may
perform data processing and other operations used to provide
on-demand services. Communication with the pods may be conducted
via pod switches 832 and 836. Components of the on-demand service
environment may communicate with a database storage system 856 via
a database firewall 848 and a database switch 852.
[0094] As shown in FIGS. 8A and 8B, accessing an on-demand service
environment may involve communications transmitted among a variety
of different hardware and/or software components. Further, the
on-demand service environment 800 is a simplified representation of
an actual on-demand service environment. For example, while only
one or two devices of each type are shown in FIGS. 8A and 8B, some
embodiments of an on-demand service environment may include
anywhere from one to many devices of each type. Also, the on-demand
service environment need not include each device shown in FIGS. 8A
and 8B, or may include additional devices not shown in FIGS. 8A and
8B.
[0095] Moreover, one or more of the devices in the on-demand
service environment 800 may be implemented on the same physical
device or on different hardware. Some devices may be implemented
using hardware or a combination of hardware and software. Thus,
terms such as "data processing apparatus," "machine," "server" and
"device" as used herein are not limited to a single hardware
device, but rather include any hardware and software configured to
provide the described functionality.
[0096] The cloud 804 is intended to refer to a data network or
plurality of data networks, often including the Internet. Client
machines located in the cloud 804 may communicate with the
on-demand service environment to access services provided by the
on-demand service environment. For example, client machines may
access the on-demand service environment to retrieve, store, edit,
and/or process information.
[0097] In some embodiments, the edge routers 808 and 812 route
packets between the cloud 804 and other components of the on-demand
service environment 800. The edge routers 808 and 812 may employ
the Border Gateway Protocol (BGP). The BGP is the core routing
protocol of the Internet. The edge routers 808 and 812 may maintain
a table of IP networks or `prefixes` which designate network
reachability among autonomous systems on the Internet.
[0098] In one or more embodiments, the firewall 816 may protect the
inner components of the on-demand service environment 800 from
Internet traffic. The firewall 816 may block, permit, or deny
access to the inner components of the on-demand service environment
800 based upon a set of rules and other criteria. The firewall 816
may act as one or more of a packet filter, an application gateway,
a stateful filter, a proxy server, or any other type of
firewall.
[0099] In some embodiments, the core switches 820 and 824 are
high-capacity switches that transfer packets within the on-demand
service environment 800. The core switches 820 and 824 may be
configured as network bridges that quickly route data between
different components within the on-demand service environment. In
some embodiments, the use of two or more core switches 820 and 824
may provide redundancy and/or reduced latency.
[0100] In some embodiments, the pods 840 and 844 may perform the
core data processing and service functions provided by the
on-demand service environment. Each pod may include various types
of hardware and/or software computing resources. An example of the
pod architecture is discussed in greater detail with reference to
FIG. 8B.
[0101] In some embodiments, communication between the pods 840 and
844 may be conducted via the pod switches 832 and 836. The pod
switches 832 and 836 may facilitate communication between the pods
840 and 844 and client machines located in the cloud 804, for
example via core switches 820 and 824. Also, the pod switches 832
and 836 may facilitate communication between the pods 840 and 844
and the database storage 856.
[0102] In some embodiments, the load balancer 828 may distribute
workload between the pods 840 and 844. Balancing the on-demand
service requests between the pods may assist in improving the use
of resources, increasing throughput, reducing response times,
and/or reducing overhead. The load balancer 828 may include
multilayer switches to analyze and forward traffic.
[0103] In some embodiments, access to the database storage 856 may
be guarded by a database firewall 848. The database firewall 848
may act as a computer application firewall operating at the
database application layer of a protocol stack. The database
firewall 848 may protect the database storage 856 from application
attacks such as structure query language (SQL) injection, database
rootkits, and unauthorized information disclosure.
[0104] In some embodiments, the database firewall 848 may include a
host using one or more forms of reverse proxy services to proxy
traffic before passing it to a gateway router. The database
firewall 848 may inspect the contents of database traffic and block
certain content or database requests. The database firewall 848 may
work on the SQL application level atop the TCP/IP stack, managing
applications' connection to the database or SQL management
interfaces as well as intercepting and enforcing packets traveling
to or from a database network or application interface.
[0105] In some embodiments, communication with the database storage
system 856 may be conducted via the database switch 852. The
multi-tenant database system 856 may include more than one hardware
and/or software components for handling database queries.
Accordingly, the database switch 852 may direct database queries
transmitted by other components of the on-demand service
environment (e.g., the pods 840 and 844) to the correct components
within the database storage system 856. In some embodiments, the
database storage system 856 is an on-demand database system shared
by many different organizations. The on-demand database system may
employ a multi-tenant approach, a virtualized approach, or any
other type of database approach. An on-demand database system is
discussed in greater detail with reference to FIGS. 9 and 10.
[0106] FIG. 8B shows a system diagram illustrating the architecture
of the pod 844, in accordance with one embodiment. The pod 844 may
be used to render services to a user of the on-demand service
environment 800. In some embodiments, each pod may include a
variety of servers and/or other systems. The pod 844 includes one
or more content batch servers 864, content search servers 868,
query servers 872, file force servers 876, access control system
(ACS) servers 880, batch servers 884, and app servers 888. Also,
the pod 844 includes database instances 890, quick file systems
(QFS) 892, and indexers 894. In one or more embodiments, some or
all communication between the servers in the pod 844 may be
transmitted via the switch 836.
[0107] In some embodiments, the application servers 888 may include
a hardware and/or software framework dedicated to the execution of
procedures (e.g., programs, routines, scripts) for supporting the
construction of applications provided by the on-demand service
environment 800 via the pod 844. Some such procedures may include
operations for providing the services described herein. The content
batch servers 864 may requests internal to the pod. These requests
may be long-running and/or not tied to a particular customer. For
example, the content batch servers 864 may handle requests related
to log mining, cleanup work, and maintenance tasks.
[0108] The content search servers 868 may provide query and indexer
functions. For example, the functions provided by the content
search servers 868 may allow users to search through content stored
in the on-demand service environment. The Fileforce servers 876 may
manage requests information stored in the Fileforce storage 878.
The Fileforce storage 878 may store information such as documents,
images, and basic large objects (BLOBs). By managing requests for
information using the Fileforce servers 876, the image footprint on
the database may be reduced.
[0109] The query servers 872 may be used to retrieve information
from one or more file systems. For example, the query system 872
may receive requests for information from the app servers 888 and
then transmit information queries to the NFS 896 located outside
the pod. The pod 844 may share a database instance 890 configured
as a multi-tenant environment in which different organizations
share access to the same database. Additionally, services rendered
by the pod 844 may require various hardware and/or software
resources. In some embodiments, the ACS servers 880 may control
access to data, hardware resources, or software resources.
[0110] In some embodiments, the batch servers 884 may process batch
jobs, which are used to run tasks at specified times. Thus, the
batch servers 884 may transmit instructions to other servers, such
as the app servers 888, to trigger the batch jobs. In some
embodiments, the QFS 892 may be an open source file system
available from Sun Microsystems.RTM. of Santa Clara, Calif. The QFS
may serve as a rapid-access file system for storing and accessing
information available within the pod 844. The QFS 892 may support
some volume management capabilities, allowing many disks to be
grouped together into a file system. File system metadata can be
kept on a separate set of disks, which may be useful for streaming
applications where long disk seeks cannot be tolerated. Thus, the
QFS system may communicate with one or more content search servers
868 and/or indexers 894 to identify, retrieve, move, and/or update
data stored in the network file systems 896 and/or other storage
systems.
[0111] In some embodiments, one or more query servers 872 may
communicate with the NFS 896 to retrieve and/or update information
stored outside of the pod 844. The NFS 896 may allow servers
located in the pod 844 to access information to access files over a
network in a manner similar to how local storage is accessed. In
some embodiments, queries from the query servers 822 may be
transmitted to the NFS 896 via the load balancer 820, which may
distribute resource requests over various resources available in
the on-demand service environment. The NFS 896 may also communicate
with the QFS 892 to update the information stored on the NFS 896
and/or to provide information to the QFS 892 for use by servers
located within the pod 844.
[0112] In some embodiments, the pod may include one or more
database instances 890. The database instance 890 may transmit
information to the QFS 892. When information is transmitted to the
QFS, it may be available for use by servers within the pod 844
without requiring an additional database call. In some embodiments,
database information may be transmitted to the indexer 894. Indexer
894 may provide an index of information available in the database
890 and/or QFS 892. The index information may be provided to file
force servers 876 and/or the QFS 892.
[0113] FIG. 9 shows a block diagram of an environment 910 wherein
an on-demand database service might be used, in accordance with
some embodiments. Environment 910 includes an on-demand database
service 916. User system 912 may be any machine or system that is
used by a user to access a database user system. For example, any
of user systems 912 can be a handheld computing system, a mobile
phone, a laptop computer, a work station, and/or a network of
computing systems. As illustrated in FIGS. 9 and 10, user systems
912 might interact via a network 914 with the on-demand database
service 916.
[0114] An on-demand database service, such as system 916, is a
database system that is made available to outside users that do not
need to necessarily be concerned with building and/or maintaining
the database system, but instead may be available for their use
when the users need the database system (e.g., on the demand of the
users). Some on-demand database services may store information from
one or more tenants stored into tables of a common database image
to form a multi-tenant database system (MTS). Accordingly,
"on-demand database service 916" and "system 916" will be used
interchangeably herein. A database image may include one or more
database objects. A relational database management system (RDBMS)
or the equivalent may execute storage and retrieval of information
against the database object(s). Application platform 918 may be a
framework that allows the applications of system 916 to run, such
as the hardware and/or software, e.g., the operating system. In an
implementation, on-demand database service 916 may include an
application platform 918 that enables creation, managing and
executing one or more applications developed by the provider of the
on-demand database service, users accessing the on-demand database
service via user systems 912, or third party application developers
accessing the on-demand database service via user systems 912.
[0115] One arrangement for elements of system 916 is shown in FIG.
9, including a network interface 920, application platform 918,
tenant data storage 922 for tenant data 923, system data storage
924 for system data 925 accessible to system 916 and possibly
multiple tenants, program code 926 for implementing various
functions of system 916, and a process space 928 for executing MTS
system processes and tenant-specific processes, such as running
applications as part of an application hosting service. Additional
processes that may execute on system 916 include database indexing
processes.
[0116] The users of user systems 912 may differ in their respective
capacities, and the capacity of a particular user system 912 might
be entirely determined by permissions (permission levels) for the
current user. For example, where a call center agent is using a
particular user system 912 to interact with system 916, the user
system 912 has the capacities allotted to that call center agent.
However, while an administrator is using that user system to
interact with system 916, that user system has the capacities
allotted to that administrator. In systems with a hierarchical role
model, users at one permission level may have access to
applications, data, and database information accessible by a lower
permission level user, but may not have access to certain
applications, database information, and data accessible by a user
at a higher permission level. Thus, different users may have
different capabilities with regard to accessing and modifying
application and database information, depending on a user's
security or permission level.
[0117] Network 914 is any network or combination of networks of
devices that communicate with one another. For example, network 914
can be any one or any combination of a LAN (local area network),
WAN (wide area network), telephone network, wireless network,
point-to-point network, star network, token ring network, hub
network, or other appropriate configuration. As the most common
type of computer network in current use is a TCP/IP (Transfer
Control Protocol and Internet Protocol) network (e.g., the
Internet), that network will be used in many of the examples
herein. However, it should be understood that the networks used in
some embodiments are not so limited, although TCP/IP is a
frequently implemented protocol.
[0118] User systems 912 might communicate with system 916 using
TCP/IP and, at a higher network level, use other common Internet
protocols to communicate, such as HTTP, FTP, AFS, WAP, etc. In an
example where HTTP is used, user system 912 might include an HTTP
client commonly referred to as a "browser" for sending and
receiving HTTP messages to and from an HTTP server at system 916.
Such an HTTP server might be implemented as the sole network
interface between system 916 and network 914, but other techniques
might be used as well or instead. In some embodiments, the
interface between system 916 and network 914 includes load sharing
functionality, such as round-robin HTTP request distributors to
balance loads and distribute incoming HTTP requests evenly over a
plurality of servers. At least as for the users that are accessing
that server, each of the plurality of servers has access to the
MTS' data; however, other alternative configurations may be used
instead.
[0119] In some embodiments, system 916, shown in FIG. 9, implements
a web-based customer relationship management (CRM) system. For
example, in some embodiments, system 916 includes application
servers configured to implement and execute CRM software
applications as well as provide related data, code, forms, web
pages and other information to and from user systems 912 and to
store to, and retrieve from, a database system related data,
objects, and Webpage content. With a multi-tenant system, data for
multiple tenants may be stored in the same physical database
object, however, tenant data typically is arranged so that data of
one tenant is kept logically separate from that of other tenants so
that one tenant does not have access to another tenant's data,
unless such data is expressly shared. In certain embodiments,
system 916 implements applications other than, or in addition to, a
CRM application. For example, system 916 may provide tenant access
to multiple hosted (standard and custom) applications. User (or
third party developer) applications, which may or may not include
CRM, may be supported by the application platform 918, which
manages creation, storage of the applications into one or more
database objects and executing of the applications in a virtual
machine in the process space of the system 916.
[0120] Each user system 912 could include a desktop personal
computer, workstation, laptop, PDA, cell phone, or any wireless
access protocol (WAP) enabled device or any other computing system
capable of interfacing directly or indirectly to the Internet or
other network connection. User system 912 typically runs an HTTP
client, e.g., a browsing program, such as Microsoft's Internet
Explorer.RTM. browser, Mozilla's Firefox.RTM. browser, Opera's
browser, or a WAP-enabled browser in the case of a cell phone, PDA
or other wireless device, or the like, allowing a user (e.g.,
subscriber of the multi-tenant database system) of user system 912
to access, process and view information, pages and applications
available to it from system 916 over network 914.
[0121] Each user system 912 also typically includes one or more
user interface devices, such as a keyboard, a mouse, trackball,
touch pad, touch screen, pen or the like, for interacting with a
graphical user interface (GUI) provided by the browser on a display
(e.g., a monitor screen, LCD display, etc.) in conjunction with
pages, forms, applications and other information provided by system
916 or other systems or servers. For example, the user interface
device can be used to access data and applications hosted by system
916, and to perform searches on stored data, and otherwise allow a
user to interact with various GUI pages that may be presented to a
user. As discussed above, embodiments are suitable for use with the
Internet, which refers to a specific global internetwork of
networks. However, it should be understood that other networks can
be used instead of the Internet, such as an intranet, an extranet,
a virtual private network (VPN), a non-TCP/IP based network, any
LAN or WAN or the like.
[0122] According to some embodiments, each user system 912 and all
of its components are operator configurable using applications,
such as a browser, including computer code run using a central
processing unit such as an Intel Pentium.RTM. processor or the
like. Similarly, system 916 (and additional instances of an MTS,
where more than one is present) and all of their components might
be operator configurable using application(s) including computer
code to run using a central processing unit such as processor
system 917, which may include an Intel Pentium.RTM. processor or
the like, and/or multiple processor units.
[0123] A computer program product implementation includes a
machine-readable storage medium (media) having instructions stored
thereon/in which can be used to program a computer to perform any
of the processes of the embodiments described herein. Computer code
for operating and configuring system 916 to intercommunicate and to
process web pages, applications and other data and media content as
described herein are preferably downloaded and stored on a hard
disk, but the entire program code, or portions thereof, may also be
stored in any other volatile or non-volatile memory medium or
device, such as a ROM or RAM, or provided on any media capable of
storing program code, such as any type of rotating media including
floppy disks, optical discs, digital versatile disk (DVD), compact
disk (CD), microdrive, and magneto-optical disks, and magnetic or
optical cards, nanosystems (including molecular memory ICs), or any
type of media or device suitable for storing instructions and/or
data. Additionally, the entire program code, or portions thereof,
may be transmitted and downloaded from a software source over a
transmission medium, e.g., over the Internet, or from another
server, or transmitted over any other conventional network
connection (e.g., extranet, VPN, LAN, etc.) using any communication
medium and protocols (e.g., TCP/IP, HTTP, HTTPS, Ethernet, etc.).
It will also be appreciated that computer code for implementing
embodiments can be implemented in any programming language that can
be executed on a client system and/or server or server system such
as, for example, C, C++, HTML, any other markup language, Java.TM.,
JavaScript.RTM., ActiveX.RTM., any other scripting language, such
as VBScript, and many other programming languages as are well known
may be used. (Java.TM. is a trademark of Sun Microsystems.RTM.,
Inc.).
[0124] According to some embodiments, each system 916 is configured
to provide web pages, forms, applications, data and media content
to user (client) systems 912 to support the access by user systems
912 as tenants of system 916. As such, system 916 provides security
mechanisms to keep each tenant's data separate unless the data is
shared. If more than one MTS is used, they may be located in close
proximity to one another (e.g., in a server farm located in a
single building or campus), or they may be distributed at locations
remote from one another (e.g., one or more servers located in city
A and one or more servers located in city B). As used herein, each
MTS could include logically and/or physically connected servers
distributed locally or across one or more geographic locations.
Additionally, the term "server" is meant to include a computing
system, including processing hardware and process space(s), and an
associated storage system and database application (e.g., OODBMS or
RDBMS) as is well known in the art.
[0125] It should also be understood that "server system" and
"server" are often used interchangeably herein. Similarly, the
database object described herein can be implemented as single
databases, a distributed database, a collection of distributed
databases, a database with redundant online or offline backups or
other redundancies, etc., and might include a distributed database
or storage network and associated processing intelligence.
[0126] FIG. 10 also shows a block diagram of environment 910
further illustrating system 916 and various interconnections, in
accordance with some embodiments. FIG. 10 shows that user system
912 may include processor system 912A, memory system 912B, input
system 912C, and output system 912D. FIG. 10 shows network 914 and
system 916. FIG. 10 also shows that system 916 may include tenant
data storage 922, tenant data 923, system data storage 924, system
data 925, User Interface (UI) 1030, Application Program Interface
(API) 1032, PL/SOQL 1034, save routines 1036, application setup
mechanism 1038, applications servers 10001-1000N, system process
space 1002, tenant process spaces 1004, tenant management process
space 1010, tenant storage area 1012, user storage 1014, and
application metadata 1016. In other embodiments, environment 910
may not have the same elements as those listed above and/or may
have other elements instead of, or in addition to, those listed
above.
[0127] User system 912, network 914, system 916, tenant data
storage 922, and system data storage 924 were discussed above in
FIG. 9. Regarding user system 912, processor system 912A may be any
combination of processors. Memory system 912B may be any
combination of one or more memory devices, short term, and/or long
term memory. Input system 912C may be any combination of input
devices, such as keyboards, mice, trackballs, scanners, cameras,
and/or interfaces to networks. Output system 912D may be any
combination of output devices, such as monitors, printers, and/or
interfaces to networks. As shown by FIG. 10, system 916 may include
a network interface 920 (of FIG. 9) implemented as a set of HTTP
application servers 1000, an application platform 918, tenant data
storage 922, and system data storage 924. Also shown is system
process space 1002, including individual tenant process spaces 1004
and a tenant management process space 1010. Each application server
1000 may be configured to tenant data storage 922 and the tenant
data 923 therein, and system data storage 924 and the system data
925 therein to serve requests of user systems 912. The tenant data
923 might be divided into individual tenant storage areas 1012,
which can be either a physical arrangement and/or a logical
arrangement of data. Within each tenant storage area 1012, user
storage 1014 and application metadata 1016 might be similarly
allocated for each user. For example, a copy of a user's most
recently used (MRU) items might be stored to user storage 1014.
Similarly, a copy of MRU items for an entire organization that is a
tenant might be stored to tenant storage area 1012. A UI 1030
provides a user interface and an API 1032 provides an application
programmer interface to system 916 resident processes to users
and/or developers at user systems 912. The tenant data and the
system data may be stored in various databases, such as Oracle.TM.
databases.
[0128] Application platform 918 includes an application setup
mechanism 1038 that supports application developers' creation and
management of applications, which may be saved as metadata into
tenant data storage 922 by save routines 1036 for execution by
subscribers as tenant process spaces 1004 managed by tenant
management process 1010 for example. Invocations to such
applications may be coded using PL/SOQL 34 that provides a
programming language style interface extension to API 1032. A
detailed description of some PL/SOQL language embodiments is
discussed in commonly assigned U.S. Pat. No. 7,730,478, titled
METHOD AND SYSTEM FOR ALLOWING ACCESS TO DEVELOPED APPLICATIONS VIA
A MULTI-TENANT ON-DEMAND DATABASE SERVICE, by Craig Weissman, filed
Sep. 21, 2007, which is hereby incorporated by reference in its
entirety and for all purposes. Invocations to applications may be
detected by system processes, which manage retrieving application
metadata 1016 for the subscriber making the invocation and
executing the metadata as an application in a virtual machine.
[0129] Each application server 1000 may be communicably coupled to
database systems, e.g., having access to system data 925 and tenant
data 923, via a different network connection. For example, one
application server 10001 might be coupled via the network 914
(e.g., the Internet), another application server 1000N-1 might be
coupled via a direct network link, and another application server
1000N might be coupled by yet a different network connection.
Transfer Control Protocol and Internet Protocol (TCP/IP) are
typical protocols for communicating between application servers
1000 and the database system. However, other transport protocols
may be used to optimize the system depending on the network
interconnect used.
[0130] In certain embodiments, each application server 1000 is
configured to handle requests for any user associated with any
organization that is a tenant. Because it is desirable to be able
to add and remove application servers from the server pool at any
time for any reason, there is preferably no server affinity for a
user and/or organization to a specific application server 1000. In
some embodiments, therefore, an interface system implementing a
load balancing function (e.g., an F5 Big-IP load balancer) is
communicably coupled between the application servers 1000 and the
user systems 912 to distribute requests to the application servers
1000. In some embodiments, the load balancer uses a least
connections algorithm to route user requests to the application
servers 1000. Other examples of load balancing algorithms, such as
round robin and observed response time, also can be used. For
example, in certain embodiments, three consecutive requests from
the same user could hit three different application servers 1000,
and three requests from different users could hit the same
application server 1000. In this manner, system 916 is
multi-tenant, wherein system 916 handles storage of, and access to,
different objects, data and applications across disparate users and
organizations.
[0131] As an example of storage, one tenant might be a company that
employs a sales force where each call center agent uses system 916
to manage their sales process. Thus, a user might maintain contact
data, leads data, customer follow-up data, performance data, goals
and progress data, etc., all applicable to that user's personal
sales process (e.g., in tenant data storage 922). In an example of
a MTS arrangement, since all of the data and the applications to
access, view, modify, report, transmit, calculate, etc., can be
maintained and accessed by a user system having nothing more than
network access, the user can manage his or her sales efforts and
cycles from any of many different user systems. For example, if a
call center agent is visiting a customer and the customer has
Internet access in their lobby, the call center agent can obtain
critical updates as to that customer while waiting for the customer
to arrive in the lobby.
[0132] While each user's data might be separate from other users'
data regardless of the employers of each user, some data might be
organization-wide data shared or accessible by a plurality of users
or all of the users for a given organization that is a tenant.
Thus, there might be some data structures managed by system 916
that are allocated at the tenant level while other data structures
might be managed at the user level. Because an MTS might support
multiple tenants including possible competitors, the MTS should
have security protocols that keep data, applications, and
application use separate. Also, because many tenants may opt for
access to an MTS rather than maintain their own system, redundancy,
up-time, and backup are additional functions that may be
implemented in the MTS. In addition to user-specific data and
tenant specific data, system 916 might also maintain system level
data usable by multiple tenants or other data. Such system level
data might include industry reports, news, postings, and the like
that are sharable among tenants.
[0133] In certain embodiments, user systems 912 (which may be
client machines/systems) communicate with application servers 1000
to request and update system-level and tenant-level data from
system 916 that may require sending one or more queries to tenant
data storage 922 and/or system data storage 924. System 916 (e.g.,
an application server 1000 in system 916) automatically generates
one or more SQL statements (e.g., SQL queries) that are designed to
access the desired information. System data storage 924 may
generate query plans to access the requested data from the
database.
[0134] Each database can generally be viewed as a collection of
objects, such as a set of logical tables, containing data fitted
into predefined categories. A "table" is one representation of a
data object, and may be used herein to simplify the conceptual
description of objects and custom objects according to some
embodiments. It should be understood that "table" and "object" may
be used interchangeably herein. Each table generally contains one
or more data categories logically arranged as columns or fields in
a viewable schema. Each row or record of a table contains an
instance of data for each category defined by the fields. For
example, a CRM database may include a table that describes a
customer with fields for basic contact information such as name,
address, phone number, fax number, etc. Another table might
describe a purchase order, including fields for information such as
customer, product, sale price, date, etc. In some multi-tenant
database systems, standard entity tables might be provided for use
by all tenants. For CRM database applications, such standard
entities might include tables for account, contact, lead, and
opportunity data, each containing pre-defined fields. It should be
understood that the word "entity" may also be used interchangeably
herein with "object" and "table".
[0135] In some multi-tenant database systems, tenants may be
allowed to create and store custom objects, or they may be allowed
to customize standard entities or objects, for example by creating
custom fields for standard objects, including custom index fields.
U.S. Pat. No. 7,779,039, titled CUSTOM ENTITIES AND FIELDS IN A
MULTI-TENANT DATABASE SYSTEM, by Weissman, et al., and which is
hereby incorporated by reference in its entirety and for all
purposes, teaches systems and methods for creating custom objects
as well as customizing standard objects in a multi-tenant database
system. In some embodiments, for example, all custom entity data
rows are stored in a single multi-tenant physical table, which may
contain multiple logical tables per organization. In some
embodiments, multiple "tables" for a single customer may actually
be stored in one large table and/or in the same table as the data
of other customers.
[0136] These and other aspects of the disclosure may be implemented
by various types of hardware, software, firmware, etc. For example,
some features of the disclosure may be implemented, at least in
part, by machine-readable media that include program instructions,
state information, etc., for performing various operations
described herein. Examples of program instructions include both
machine code, such as produced by a compiler, and files containing
higher-level code that may be executed by the computer using an
interpreter. Examples of machine-readable media include, but are
not limited to, magnetic media such as hard disks, floppy disks,
and magnetic tape; optical media such as CD-ROM disks;
magneto-optical media; and hardware devices that are specially
configured to store and perform program instructions, such as
read-only memory devices ("ROM") and random access memory
("RAM").
[0137] While one or more embodiments and techniques are described
with reference to an implementation in which a service cloud
console is implemented in a system having an application server
providing a front end for an on-demand database service capable of
supporting multiple tenants, the one or more embodiments and
techniques are not limited to multi-tenant databases nor deployment
on application servers. Embodiments may be practiced using other
database architectures, i.e., ORACLE.RTM., DB2.RTM. by IBM and the
like without departing from the scope of the embodiments
claimed.
[0138] Any of the above embodiments may be used alone or together
with one another in any combination. Although various embodiments
may have been motivated by various deficiencies with the prior art,
which may be discussed or alluded to in one or more places in the
specification, the embodiments do not necessarily address any of
these deficiencies. In other words, different embodiments may
address different deficiencies that may be discussed in the
specification. Some embodiments may only partially address some
deficiencies or just one deficiency that may be discussed in the
specification, and some embodiments may not address any of these
deficiencies.
[0139] While various embodiments have been described herein, it
should be understood that they have been presented by way of
example only, and not limitation. Thus, the breadth and scope of
the present application should not be limited by any of the
embodiments described herein, but should be defined only in
accordance with the following and later-submitted claims and their
equivalents.
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